LZW (Lempel-Ziv-Welch) is a universal lossless data compression algorithm, which takes linear time in encoding and decoding. This paper discusses a methodology to reduce time complexity by combining binary search with LZW. The existing LZW compression algorithm takes large time for dictionary creation while encoding and decoding. By using binary search with LZW the time complexity can be reduced optimally and gradually because the comparison ratio is less while creating the dictionary. Especially while compressing the search for patterns in the table and also in the decompression algorithm for finding the pattern in the table is taking linear time for searching. Therefore, combining Enhanced LZW with binary search reduces the time complexity. The proposed methodology may be bust in data compression for communication, Maximizes the reduction of complexity in pattern identification for compression. The proposed methodology reduces the complexity in time with Binary search tree (BST). The experimental result shows 94.21 % improvement on Compression and 93.34% improvement on Decompression.

Data compression is the art of converting a data stream into a small in size data bits so that it can be easily travel a long distance without increasing load of its volume on a constant Bandwidth channel regardless of its increase volume. Data compression is essential techniques since last[1]...

We study a new technique for optimal data compression subject to conditions of causality and different types of memory. The technique is based on the assumption that some information about compressed data can be obtained from a solution of the associated problem without constraints of causality...

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The development of an efficient compression scheme to process the Arabic language represents a difficult task. This paper employs the dynamic Huffman coding on data compression with variable length bit coding, on the Arabic language. Experimental tests have been performed on both Arabic and...

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